257 research outputs found
Zukunftskonzept Harz : eine Untersuchung zur zukünftigen Anpassung des Wintertourismus an den Klimawandel
Der Harz ist ein deutsches Mittelgebirge dessen Haupterwerbsquelle der Tourismus ist. Diese Arbeit befasst sich mit dem Umgang der durch den Klimawandel verursachten Gefährdung des Wintertourismus. Die steigenden Temperaturen und Niederschlagsveränderungen führen zu immer häufigeren schneefreien Tagen während der Wintersaison und stellen eine große Gefahr für die Erhaltung des Wintertourismus im Harz dar. Anpassungsmaßnahmen- und Strategien wie der Einsatz von Schneekanonen werden stark diskutiert. Viele sehen den Gebrauch von künstlichem Schnee als einzige Möglichkeit auch in Zukunft eine gute Wintersaison und somit auch eine wichtige Einnahmequelle erhalten zu können. Kunstschneegegner hingegen sehen dieser Entwicklung mit großer Besorgnis entgegen. Hohe Kosten, ein maßloser Wasserverbrauch und der rücksichtslose Eingriff in die Natur werden hingenommen und das Ergebnis wird auf den Schulter der nächsten Generationen ausgetragen. Ein Blick auf die tatsächlichen Möglichkeiten des Harzes Kunstschnee zu benutzen und auch die Aussicht auf die demografische Entwicklung bezüglich der zukünftigen Zielgruppen zeigen, dass künstlicher Schnee die Zukunft des Harzer Wintertourismus nicht sichern kann
A computational framework to emulate the human perspective in flow cytometric data analysis
Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation.
<p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods.
<p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics
Redox proteomics of the inflammatory secretome identifies a common set of redoxins and other glutathionylated proteins released in inflammation, influenza virus infection and oxidative stress
Protein cysteines can form transient disulfides with glutathione (GSH), resulting in the production of glutathionylated proteins, and this process is regarded as a mechanism by which the redox state of the cell can regulate protein function. Most studies on redox regulation of immunity have focused on intracellular proteins. In this study we have used redox proteomics to identify those proteins released in glutathionylated form by macrophages stimulated with lipopolysaccharide (LPS) after pre-loading the cells with biotinylated GSH. Of the several proteins identified in the redox secretome, we have selected a number for validation. Proteomic analysis indicated that LPS stimulated the release of peroxiredoxin (PRDX) 1, PRDX2, vimentin (VIM), profilin1 (PFN1) and thioredoxin 1 (TXN1). For PRDX1 and TXN1, we were able to confirm that the released protein is glutathionylated. PRDX1, PRDX2 and TXN1 were also released by the human pulmonary epithelial cell line, A549, infected with influenza virus. The release of the proteins identified was inhibited by the anti-inflammatory glucocorticoid, dexamethasone (DEX), which also inhibited tumor necrosis factor (TNF)-α release, and by thiol antioxidants (N-butanoyl GSH derivative, GSH-C4, and N-acetylcysteine (NAC), which did not affect TNF-α production. The proteins identified could be useful as biomarkers of oxidative stress associated with inflammation, and further studies will be required to investigate if the extracellular forms of these proteins has immunoregulatory functions
Gene Expression Analysis of In Vivo Fluorescent Cells
BACKGROUND: The analysis of gene expression for tissue homogenates is of limited value because of the considerable cell heterogeneity in tissues. However, several methods are available to isolate a cell type of interest from a complex tissue, the most reliable one being Laser Microdissection (LMD). Cells may be distinguished by their morphology or by specific antigens, but the obligatory staining often results in RNA degradation. Alternatively, particular cell types can be detected in vivo by expression of fluorescent proteins from cell type-specific promoters. METHODOLOGY/PRINCIPAL FINDINGS: We developed a technique for fixing in vivo fluorescence in brain cells and isolating them by LMD followed by an optimized RNA isolation procedure. RNA isolated from these cells was of equal quality as from unfixed frozen tissue, with clear 28S and 18S rRNA bands of a mass ratio of approximately 2ratio1. We confirmed the specificity of the amplified RNA from the microdissected fluorescent cells as well as its usefulness and reproducibility for microarray hybridization and quantitative real-time PCR (qRT-PCR). CONCLUSIONS/SIGNIFICANCE: Our technique guarantees the isolation of sufficient high quality RNA obtained from specific cell populations of the brain expressing soluble fluorescent marker, which is a critical prerequisite for subsequent gene expression studies by microarray analysis or qRT-PCR
Current status of turbulent dynamo theory: From large-scale to small-scale dynamos
Several recent advances in turbulent dynamo theory are reviewed. High
resolution simulations of small-scale and large-scale dynamo action in periodic
domains are compared with each other and contrasted with similar results at low
magnetic Prandtl numbers. It is argued that all the different cases show
similarities at intermediate length scales. On the other hand, in the presence
of helicity of the turbulence, power develops on large scales, which is not
present in non-helical small-scale turbulent dynamos. At small length scales,
differences occur in connection with the dissipation cutoff scales associated
with the respective value of the magnetic Prandtl number. These differences are
found to be independent of whether or not there is large-scale dynamo action.
However, large-scale dynamos in homogeneous systems are shown to suffer from
resistive slow-down even at intermediate length scales. The results from
simulations are connected to mean field theory and its applications. Recent
work on helicity fluxes to alleviate large-scale dynamo quenching, shear
dynamos, nonlocal effects and magnetic structures from strong density
stratification are highlighted. Several insights which arise from analytic
considerations of small-scale dynamos are discussed.Comment: 36 pages, 11 figures, Spa. Sci. Rev., submitted to the special issue
"Magnetism in the Universe" (ed. A. Balogh
Irf4 is a positional and functional candidate gene for the control of serum IgM levels in the mouse
Natural IgM are involved in numerous immunological functions but the genetic factors that control the homeostasis of its
secretion and upholding remain unknown. Prompted by the finding that C57BL/6 mice had significantly lower serum levels of
IgM when compared with BALB/c mice, we performed a genome-wide screen and found that the level of serum IgM was
controlled by a QTL on chromosome 13 reaching the highest level of association at marker D13Mit266 (LOD score¼3.54).
This locus was named IgMSC1 and covered a region encompassing the interferon-regulatory factor 4 gene (Irf4). The number
of splenic mature B cells in C57BL/6 did not differ from BALB/c mice but we found that low serum levels of IgM in C57BL/6 mice
correlated with lower frequency of IgM-secreting cells in the spleen and in the peritoneal cavity. These results suggested that
C57BL/6 mice have lower efficiency in late B-cell maturation, a process that is highly impaired in Irf4 knockout mice. In fact, we
also found reduced Irf4 gene expression in B cells of C57BL/6 mice. Thus, we propose Irf4 as a candidate for the IgMSC1
locus, which controls IgM homeostatic levels at the level of B-cell terminal differentiation
Complex Aggregates over Clusters of Elements
Complex aggregates have been proposed as a way to bridge the gap between approaches that handle sets by imposing conditions on specific elements, and approaches that handle them by imposing conditions on aggregated values. A complex aggregate summarises a subset of the elements in a set, where this subset is defined by conditions on the attribute values. In this paper, we present a new type of complex aggregate, where this subset is defined to be a cluster of the set. This is useful if subsets that are relevant for the task at hand are difficult to describe in terms of attribute conditions. This work is motivated from the analysis of flow cytometry data, where the sets are cells, and the subsets are cell populations. We describe two approaches to aggregate over clusters on an abstract level, and validate one of them empirically, motivating future research in this direction
Treatment of displaced intra-articular calcaneal fractures by ligamentotaxis: current concepts’ review
Introduction: A large variety of therapeutic modalities for calcaneal fractures have been described in the literature. No single treatment modality for displaced intra-articular calcaneal fractures has proven superior over the other. This review describes and compares the different percutaneous distractional approaches for intra-articular calcaneal fractures. The history, technique, anatomical and fracture considerations, limitations and the results of different distractional approaches reported in the literature are reviewed. Method: Literature review on different percutaneous distractional approaches for displaced intra-articular calcaneal fractures. Results: Eight studies in which application of a distraction technique was used for the treatment of calcaneal fractures were identified. Because of the use of different classification, techniques, and outcome scoring systems, a meta-analysis was not possible. A literature review reveals overall fair to poor result in 10-29% of patients. Ten up to 26% of patients are unable to return to work after percutaneous treatment of their fracture. A secondary arthrodesis has to be performed in 2-15% of the cases. Infectious complications occur in 2-15%. Some loss of reduction is reported in 4-67%. Conclusion: Percutaneous distractional reduction and fixation appears to be a safe technique with overall good results and an acceptable complication rate, compared with other treatment modalities for displaced intra-articular calcaneal fractures. A meta-analysis, based on Cochrane Library criteria is not possible, because of a lack of level 1 and 2 trials on this subject
Single-cell analysis tools for drug discovery and development
The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed
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